AI Risks and Benefits Scale – AIRBS
Measures individuals' perceptions of the potential risks and benefits associated with the implementation of artificial intelligence in healthcare.
Scale Development & Technical Details
Scale Overview
The AI Risks and Benefits Scale – AIRBS was developed by Sophie Kerstan, Nadine Bienefeld, & Gudela Grote (2024). It is designed to measure Risk and benefit perceptions of AI in healthcare. The scale is intended for use with Adults.
Scale Structure
This instrument consists of 19 items organized into 2 factors/subscales: Risks, Benefits.
| Factor / Subscale | Items | N |
|---|---|---|
| Risks | 1,2,3,4,5,6,7,8,9,10 | 10 |
| Benefits | 11,12,13,14,15,16,17,18,19 | 9 |
Response Format
Respondents rate each item using a custom response format.
Response anchors: 1 = Very unlikely, 2 = Unlikely, 3 = Somewhat unlikely, 4 = Neutral, 5 = Somewhat likely, 6 = Likely, 7 = Very likely.
Scoring
Items are scored by subscale, with each subscale sum representing a distinct dimension.
Total scores range from 19 to 133. Interpretation guidelines:
- Low overall perception of AI impact: 19 – 57
- Moderate overall perception of AI impact: 58 – 95
- High overall perception of AI impact: 96 – 133
Psychometric Properties
Internal Consistency: The scale has demonstrated good to excellent internal consistency with reported Cronbach’s alpha values of Tested for structure and reliability in original study.
Administration
The scale is self-administered and typically takes approximately 5 minutes to complete. It can be administered individually or in group settings. No special training is required for administration.